Emotional Communication During Crisis Events: Mining Structural OSN Patterns
Ema Kušen, Mark Strembeck
Abstract
With currently about three billion users, online social networks (OSNs) provide an important channel for people to express their opinion, seek information, and engage in discussions during events of public interest, such as disease outbreaks, natural disasters, or political elections. Human perception of such events does not only depend on the circumstances surrounding an individual but also on his <inline-formula><tex-math notation="LaTeX">$/$</tex-math></inline-formula> her attitude toward a particular event. In this context, <i>human emotions</i> play an important role. Our paper reports on an analysis of the emotions expressed on Twitter as people face various types of crisis events. We provide an overview of structural network patterns that arise as humans exchange emotional OSN messages. To this end, we analyzed a dataset including 23.31 million tweets that have been sent during 18 different crisis events which happened in 2017 and 2018 in 10 different countries.